For the declipping process in intelligent tone mapping operations (ITMO), an important operation consists in building clipped regions. These regions are composed of pixels exceeding a threshold value (clipped pixels), where adjacent pixels have similar colors. In others words, the difference of color between these adjacent clipped pixels must be below a threshold. The goal is to process similarly pixels representing a same color by including them in a region.
The difference of color can be expressed by an Euclidian distance in a color opponent space, such as the CIELAB color space. This distance can be computed as the Euclidian distance considering only the chroma in the a*b* plane (ΔC), or considering the chroma and the lightness in the L*a*b* three dimensional space (ΔE). These two metrics can be used to evaluate the difference between two colors perceived by a human being.
Unfortunately, these Euclidian distances are not compliant with the problem to be solved. In case of the declipping algorithm, it is desired to include in a region colors with similar hues, as well as specular areas, which can be completely white. However the ΔC and ΔE give a same weight/importance to a difference of chroma or a difference of hue.
By definition, the clipped regions are composed of over-exposed pixels. Some pixels of these regions can be completely over-exposed, up to the clipping (full saturation to maximum pixel value, 255 for 8 bits). In order to include these clipped pixels in the region, a big ΔC or ΔE should be accepted. But in this case, pixels with big color difference (big hue difference) would be included in the region too. Thus using these metrics, regions with different colors would be merged together.
This case is illustrated on FIG. 1, where a white pixel CW (a*=0, b*=0) must be integrated in the same region as C1 for a correct declipping, but where C2 should not (although ΔC between C1 and CW is larger than ΔC between C1 and C2).
The difference of color can be expressed in the CIELAB color space as the angle formed by the hues of the 2 color points in this space (ΔH). This is the metric that is used in the description of the declipping algorithm (Set forth in WO2015113655 and WO20151138881) The main drawback of this angular metric is that the notion of hue angle loses any sense close the origin and has no sense for white pixels (L*max, a*=0, b*=0). Thus for colors with little chroma (i.e. close to the origin in the a*b* plane), noise has a big influence on hue. This means that the hue angle difference is sensitive to noise.
FIG. 1 represents these distances ΔC and ΔH as they could be computed in the a*b* plane of the CIELAB color space. In this plane, the white color CW is located at the origin, and would not be incorporated in the clipped region with these metrics.
This disclosure is closely related to published applications WO2015113655 filed 28 Aug. 2014, entitled “METHOD FOR CONVERTING A SATURATED IMAGE INTO A NON-SATURATED IMAGE” and WO2015113881 filed 21 Jan. 2015 entitled “METHOD FOR CONVERTING A SATURATED IMAGE INTO A NON-SATURATED IMAGE” which are incorporated by reference. Specifically, this invention provides an additional method for evaluating the distance between two colors in color opponent space, such as a CIELAB color space.